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Kahneman Bingo and Gigerenzer Golf

The sport of “Kahneman bingo” has become popular at market research conferences recently. Audience members have to count the number of times Daniel Kahneman is mentioned in a talk, with bonus points if a picture of his book, Thinking Fast and Slow, appears in the slides or if the Nobel Prize or system one and two are mentioned. In one recent conference, the winning score was 18 separate mentions.

However, there’s a challenge to Kahneman’s position as the king of behavioral economics (as it happens, he doesn’t even describe his own work as behavioral economics, but that’s a different story). This challenge comes from German psychologist Gerd Gigerenzer.

The challenge is expressed in the polite academic language of the journal, but by the standards of that world, it feels like. Gigerenzer tells us that Kahneman thinks of consumers as stupid, biased, and weak-minded; that they make predictable errors that have to be corrected by benign governments and regulators. He thinks Kahneman’s approach is patronizing and disrespectful to the individual. Gigerenzer’s own view is that people are actually smarter to use mental shortcuts and heuristics than to try to solve problems in a rational, mathematical way – which is an impossible task anyway.
Kahneman only responds obliquely to this challenge – referring in his book to “our most prominent critic, a German psychologist” and suggesting that Gigerenzer himself does not do justice to the ability of people to process information. Either way, the ground-level results of the two philosophies are not so far apart. The experiments were done in the university labs of America where Kahneman’s followers mostly work, and those carried out in Germany or Switzerland by disciples of Gigerenzer, produce similar results and say similar things about how people make judgments. The worldview through which those results are interpreted is, however, quite different.
Recalling the three models I described in my, Kahneman’s approach is the heuristics and biases view, while Gigerenzer prefers the adaptive toolbox.
Kahneman, along with Thaler, Sunstein, and perhaps the majority of other behavioral economics and decision-making researchers, regularly compare the choices of their experimental subjects to an objectively optimal choice (as defined in rational choice theory, a specific field of decision theory which is also the basis of neoclassical economics). By this means they can point out how people lose out by not taking a more rational decision.
This approach works well in fields where there is a clearly defined correct choice, and where we can see objective benefits in making that choice. For example, if someone wants to save money and can choose between several options which will have a defined future cash outcome, it is reasonable to say that there may be the best choice. The conclusion for policymakers is that we can nudge consumers towards this best choice, making it easier for them to take the path to what they would want anyway.
Gigerenzer’s approach usually focuses on domains in which there is no way to find the right answer by maximizing utility. He considers situations where it’s impossible to know the correct answer (such as choosing the best stock portfolio if you don’t know how share prices are going to change) or those where the correct answer can be known but is not based on utility (such as guessing which of two cities is bigger, which of two products will best meet your needs, or how to catch a baseball).
His research aims to find out which mental shortcuts will give a good-enough solution to these problems. These shortcuts are called fast-and-frugal heuristics, and their main feature is that they use the smallest possible amount of information to make a choice. The policy conclusion Gigerenzer prefers is that we should, where necessary, teach people the heuristics that will help them to make good choices or accurate judgments. For example, doctors can be taught some simple rules that help them better understand probabilities and give patients more informed advice.
On the face of it, Gigerenzer’s approach should be more useful for market research purposes, except in a few areas such as financial regulation. If consumers do use fast-and-frugal heuristics to choose what products they buy, and if we can understand those heuristics through the research process, we will be in a good position to predict or influence the products that will succeed in the marketplace.
One challenge is that the Gigerenzer heuristics are hard to generalize, meaning that it takes a lot of psychological research to apply his approach in a new category. Take two of the heuristics he holds up as typical examples.
The “gaze heuristic” is used by baseball players to catch a ball by simply keeping the ball, and the horizon at a fixed angle while they run. But this is only useful in a very specific situation; it doesn’t even generalize to avoiding being hit by a ball (say if you’re watching a golf match), let alone to the many non-ball-related decisions that some of us have to make in life.
“Take-The-Best” is another heuristic that he talks about, which is more general; it tells us to make a choice between multiple products by comparing them only based on their most important feature. Only if the two products are indistinguishable on that feature do we look at the second most important, and so on. Nice and simple – but there is no rule to tell us which feature is most important. Should we choose chocolate bars only based on flavor, or on size, or on price, or on the number of calories? And surely each of those features might be important to different people and in different situations.
This highlights a key flaw in the Gigerenzer approach: the heuristics indeed use a minimal amount of information within the decision itself, but to choose which heuristic to use requires a large amount of meta-data about the decision and the context it takes place within. Fast-and-frugal heuristics displace the problem to another level, rather than solving it.
Kahneman’s approach similarly defers this problem: once the correct choice is well-defined, we can predict how consumers will diverge from it using the equations of prospect theory, then design nudges to push them back onto the correct path. But in practice, we usually cannot use rational choice theory to determine the correct choice, because we do not have accurate enough data about the situation or about people’s preferences.
Both of these versions of behavioral economics – heuristics and biases and the adaptive toolbox – are useful, then, but neither provides a comprehensive set of tools to understand real consumer decisions. We believe that, of the three main decision-making models, the information processing model is both the most accurate and the most amenable to practical marketing use. 

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